Solutions Architect - Langfuse

Job description

About the Role AI applications are being built faster than teams can monitor, debug, or trust them. ClickHouse recently acquired Langfuse — the leading open source LLM observability platform — making it a core part of the ClickHouse product stack. Together, ClickHouse and Langfuse offer engineering teams the most powerful combination in the market: real-time, high-performance analytics infrastructure paired with best-in-class LLM tracing, evaluation, and observability tooling. This role sits at the center of that combined story. We're looking for a Langfuse Solutions Architect who is already embedded in the AI observability ecosystem — someone who understands how engineering teams instrument and evaluate LLM applications, and can credibly represent the full ClickHouse + Langfuse platform to the teams that need it most. This is not a generalist SA role. You'll be our dedicated technical presence in the LLM observability space — opening doors through the Langfuse community, deepening relationships with AI engineering teams, and helping them get the most out of a platform that now spans from raw data infrastructure to production LLM monitoring. You'll work at the intersection of community, pre-sales, and technical advisory, and you'll be the person who makes the ClickHouse + Langfuse stack the obvious choice for teams building serious AI applications. What You'll Be Doing Pre-Sales & Technical Advisory Lead technical evaluations with AI engineering teams considering ClickHouse as their observability data store, from initial architecture review through POC and production deployment Engage directly with data engineers, ML engineers, and platform architects to understand their LLM application stack, trace volumes, evaluation workflows, and query patterns — and map those requirements to ClickHouse | Lanfguse capabilities Work across all levels of customer organizations, from individual contributors building LLM pipelines to CTOs making infrastructure decisions Design and deliver reference implementations, schema designs, and ingestion patterns optimized for LLM trace data at scale Pipeline & Revenue Contribution Source and qualify pipeline directly through ecosystem relationships and community engagement — this role is expected to open doors, not just walk through them Partner with ClickHouse AEs to progress and close opportunities within the AI and LLM observabil…